代写MGT6155 Supply Networks Management 2024帮做R编程

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Coursework Specification PGT 2023-24

Module Code: MGT6155			Coursework Code: MGT6155-1
Module Title: Supply Networks Management
Date Available: 15/02/2024
Submission details: Tuesday, 30^th April 2024, 12pm (noon) Electronic submission only through Blackboard You can submit your assignment multiple times to the submission link on the module Blackboard site. Each time you submit you will receive a Similarity Report. You can check this and improve your referencing before the final deadline. After 3 submissions you will need to wait 24 hours before you receive a new report. Please note: each new submission replaces any previous submission. It is not possible to retrieve a previous submission. Your final submission must be made before the deadline to avoid late penalties. You should note that the time of submission is taken from once the document has been successfully uploaded and confirmed – this may take more than five minutes during busy periods. Late penalties will be applied to any work submitted from 12.01pm on Tuesday 30^th April 2024 onwards. Details of how to calculate a late penalty can be found in your programme Handbook. It is your responsibility to ensure the correct document/file has uploaded successfully. When submitting you must: 1. Include a completed cover sheet (available from Blackboard) 2. Use ‘Student Number, MGT6155-1’ (e.g.190011001 MGT1655 – 1) as the document’s file name and also as the Assignment Title in Turnitin.
Contribution to Final Mark for Module: (50%)
Maximum Word Length: 1,500 words Unless otherwise specified, the word count is for the main body of the text and ignores the reference list and appendices. If you exceed the word length you will be penalised. For details see the Management School Handbooks. Please note that SUMS does not have a word count tolerance - it is a stated maximum as outlined above.
Requirements You are required to compile a detailed report following the above-mentioned indications, where the optimal solution is described for the Supply Network Management problem below. Relevant data for the parameters of the problem is provided in a datasheet. In addition, each student is assigned an individual datasheet for some of these parameters of the problem, which will make the dataset of each student unique. These are available on the MGT6155 Blackboard page. Consider a multiple-echelon Supply Network, organised as follows: In the first tier, primary products A are produced in plant As, which can be either fed into Plant Bs from the second tier, in order to produce intermediary products B, or sold on the market. Product B can be sold to customers, but is also a production input to the final product C, which in turn is produced in the third tier. Product C can be sold to customers, while plant Cs can be fed also by external sources for product B whenever convenient. At each stage, a conversion ratio is provided from input materials to products. As the manufacturing process is not perfectly reliable, only a certain percentage of the production is good. There are processing capacities and storage capacities for both raw materials and products. The objective is to find the optimal solution in terms of: Production quantities at each plant for each period; Shipments on each route for each period; Inventories at each plant for each period; with the aim to minimise the production and logistics costs, whilst meeting the required demand. In the report, you need to: ● Identify and describe the characteristics and the complexity of the appropriate Supply Chain optimisation model; ● Translate your individual datasheet into a dataset to feed the model (dataset to be included in your report as in appendix A); ● Execute the optimisation process in IBM ILOG CPLEX Optimization Studio and export the results (results to be included in your report as in appendix B); ● Describe accurately the obtained solutions and the characteristics of the computational process, explain the solutions in detail along with the underlying reasons of why these results are obtained; ● Perform. basic sensitivity analyses on the parameters as per indications in your datasheet, explain your findings along with the underlying reasons; ● Perform. what-if analyses as per indications in your datasheet, explain your findings along with the underlying reasons; ● Provide a final summary of your findings, suitable for a management report, including your relevant comments and any managerial recommendations. VERY IMPORTANT NOTES: The use of AI or Generative AI, either in full or in part, is strictly prohibited in completing the coursework. Utilizing prohibited AI tools will incur penalties as outlined in the University's Unfair Means and AI Use in Assessment Guidance. Assignments will be scrutinized for authenticity, with a specific emphasis on original thought and analysis. Violations of these guidelines will be treated as academic misconduct and will be subject to the disciplinary actions defined in the university's academic integrity policy, which includes potential failure of the assignment or course. To provide clarity, the following types of generative AI are explicitly prohibited: o AI tools that assist in the generation of content, including but not limited to text, code, visual materials, and qualitative or quantitative analysis. This prohibition includes, but is not limited to, tools such as ChatGPT and Gemini. o AI-driven tools aimed at improving English grammar, vocabulary, or spelling, such as Grammarly. o As alternatives, students are encouraged to use, for example, academic databases (e.g., Google Scholar, Star Plus Library) and online writing guides (e.g., Purdue Online Writing Lab).
Assessment criteria	Hard Fail (0-39)	Soft Fail (40-49)		Pass (50-59)	Merit (60-69)	Distinction (70-79)	Distinction (80+)
UNDERSTANDING Understanding of the case and of the underlying decision making problems	Answers to the proposed questions show a serious lack of understanding of the case and of the underlying problems	Answers to the proposed questions show a lack of understanding of the case and of the underlying problems		Answers show a sufficient degree of understanding of the case and of the underlying problems	Answers show a good degree of understanding of the case and of the underlying problems	Answers show a very good degree of understanding of the case and of the underlying problems	Answers show an excellent degree of understanding of the case and of the underlying problems
MODELING Accuracy in problem modelling and dataset production	Poor accuracy in modelling the problems is shown.	Insufficient accuracy in modelling the problems is shown.		Just a sufficient amount of accuracy in modelling the problems is shown.	A good accuracy in modelling the problems is shown	A very good accuracy in modelling the problems is shown	An excellent accuracy in modelling the problems is shown
SOLVING Accuracy in obtaining and explaining the results	Poor and not detailed explanations are provided.	Insufficient explanations are provided.		Provided explanations are endowed with sufficient clarity.	Clear explanations are provided	Very clear explanations are provided	Excellent explanations are provided
ANALYSES Accuracy in performing sensitivity and what-if analyses	No analyses are provided.	Insufficient analyses are provided.		Sufficient analyses are provided.	Good analyses are provided.	Very good analyses are provided.	Excellent analyses are provided.
MANAGEMENT Originality and accuracy in defining the managerial implications of the case studies.	No links to management implications are provided.	Poor links to management implications are provided.		Some links to management implications are provided.	Clear links to management implications are provided.	Very clear links to management implications are provided.	Excellent links to management implications are provided.
REPORT Accuracy in writing the Report	Very weak and not well organised presentation	Weak presentation with significant structure problems		Clear presentation with some structure problems	Good presentation with clear structure	Very good presentation with very clear structure	Excellent presentation with excellent structure
Referencing: you must reference your work correctly using the Harvard method. Failure to do so will result in the deduction of marks and possible proceedings under the University's Regulations as to the Use of Unfair Means
Independence of working: You are reminded of the University's Regulations on the Use of Unfair Means and academic integrity which are outlined in the School's Handbooks. If there is a suspicion that your work is not your own and that you have used unfair means or there is suspicion of a breach of academic integrity in writing this assessment then you may be referred to our unfair means officers to consider your work. Therefore, you are advised to ensure that you undertake the relevant guidance on the module site or programme level sites that you have access too. If you cannot access these, please contact the Student Experience Office.
Other Submission Details: ● Use the standard Management School cover sheet ● Have the word count given on the cover sheet ● Be presented with 2.5cm margins all round ● Use Times New Roman 12 point font for the main body text, and justify the text ● Use 1.5 line spacing ● Have all pages numbered except the first ● Be properly spell checked ● Be made attractive with suitable use of headings, paragraphs and sections ● Be properly referenced to the Management School version of Harvard referencing You are required to compile a detailed report following the above-mentioned indications. All optimisation analyses should be undertaken using IBM ILOG CPLEX. You can include screenshots from the software package, tables and charts to the report.
Resit: Resit has the same structure including the case study, the problem to be addressed and the type of report that needs to be delivered, but the students are required to use a different dataset to conduct the experiment.
Other matters: None